Idiomatic Functional Programming With DRY Python - Episode 272
Python is an intuitive and flexible language, but that versatility can also lead to problematic designs if you’re not careful. Nikita Sobolev is the CTO of Wemake Services where he works on open source projects that encourage clean coding practices and maintainable architectures. In this episode he discusses his work on the DRY Python set of libraries and how they provide an accessible interface to functional programming patterns while maintaining an idiomatic Python interface. He also shares the story behind the wemake Python styleguide plugin for Flake8 and the benefits of strict linting rules to engender good development habits. This was a great conversation about useful practices to build software that will be easy and fun to work on.
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- Your host as usual is Tobias Macey and today I’m interviewing Nikita Sobolev about his work with DRY Python and Wemake Services
- How did you get introduced to Python?
- Can you start by sharing your overarching philosophies or design aesthetics for writing maintainable software?
- What is your process for starting a new project, beginning at the design phase?
- What are some of the challenges or shortcomings that you see in the "default" way that most developers write Python?
- What is DRY Python is and how does it help in addressing those concerns?
- What was your motivation for creating these projects?
- There are a number of different projects that are being built under the DRY Python umbrella. Can you list the ones that are currently active and outline how they fit together?
- What are some of the initial challenges that newcomers to the DRY Python libraries encounter?
- How do you approach the design of the API and developer experience to make these development approaches more accessible?
- What have you seen in terms of real world impact on the maintainability and extensibility of projects that you have built on top of the DRY Python components?
- In addition to DRY Python you are also involved with development of the wemake-python-styleguide. Can you describe that projects goal and how it got started?
- If you make the linting too restrictive then developers are likely to just ignore or disable it. What have you found to be the right balance to which rules will fail a build and which are just informational?
- Why do you push the responsibility for things like formatting onto the developer, rather than an autoformatter such as YAPF or Black?
- What are some of the other supporting technologies that you rely on during your development workflow?
- What are some of the elements that you think are missing in the common toolbox for Python developers?
- What tools are we lacking entirely?
- What are the cases where DRY Python is the wrong choice?
- What are your goals and plans for the future of DRY Python and the various Wemake libraries?
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- Dotenv Linter
- Wemake Python Package Cookiecutter Template
- Test Driven Development
- Requirements Analysis
- Django Rest Framework
- Punq dependency injection library
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- Flake8 Baseline
- Pip Dependency Resolver
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- Zio Scala
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